Optimizing Microsatellite Marker Panels for Genetic Diversity and Population Genetic Studies: An Ant Colony Algorithm Approach with Polymorphic Information Content
2023
Ryan Rasoarahona | Pish Wattanadilokchatkun | Thitipong Panthum | Thanyapat Thong | Worapong Singchat | Syed Farhan Ahmad | Aingorn Chaiyes | Kyudong Han | Ekaphan Kraichak | Narongrit Muangmai | Akihiko Koga | Prateep Duengkae | Agostinho Antunes | Kornsorn Srikulnath
Microsatellites are polymorphic and cost-effective. Optimizing reduced microsatellite panels using heuristic algorithms eases budget constraints in genetic diversity and population genetic assessments. Microsatellite marker efficiency is strongly associated with its polymorphism and is quantified as the polymorphic information content (<i>PIC</i>). Nevertheless, marker selection cannot rely solely on <i>PIC</i>. In this study, the ant colony optimization (ACO) algorithm, a widely recognized optimization method, was adopted to create an enhanced selection scheme for refining microsatellite marker panels, called the <i>PIC</i>–ACO selection scheme. The algorithm was fine-tuned and validated using extensive datasets of chicken (<i>Gallus gallus</i>) and Chinese gorals (<i>Naemorhedus griseus</i>) from our previous studies. In contrast to basic optimization algorithms that stochastically initialize potential outputs, our selection algorithm utilizes the <i>PIC</i> values of markers to prime the ACO process. This increases the global solution discovery speed while reducing the likelihood of becoming trapped in local solutions. This process facilitated the acquisition of a cost-efficient and optimized microsatellite marker panel for studying genetic diversity and population genetic datasets. The established microsatellite efficiency metrics such as <i>PIC</i>, allele richness, and heterozygosity were correlated with the actual effectiveness of the microsatellite marker panel. This approach could substantially reduce budgetary barriers to population genetic assessments, breeding, and conservation programs.
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